Machine identities such as service accounts, applications and workloads often outnumber human users and operate without direct oversight. They can hold broad permissions, persist across environments and remain active long after a project changes. That creates hidden trust paths, inconsistent ownership and weak offboarding unless organisations apply identity governance, least privilege and lifecycle controls.
Why This Matters for Security Teams
Machine identities make api security harder to govern because they are not managed like people. Service accounts, workloads, and application tokens can proliferate faster than the teams that own them, and they often bypass the review, attestation, and joiner-mover-leaver processes used for human access. That leaves hidden trust paths in CI/CD, integration layers, and third-party connections that are difficult to see and even harder to revoke.
The risk is not just volume. It is persistence. Secrets, certificates, and OAuth grants can remain valid long after the original purpose has changed, especially when ownership is unclear or offboarding is manual. NHI Management Group’s Ultimate Guide to NHIs notes that only 20% of organisations have formal processes for offboarding and revoking API keys, and 97% of NHIs carry excessive privileges. That combination makes API governance look complete on paper while still leaving broad operational exposure.
Current guidance from NIST Cybersecurity Framework 2.0 supports identity governance as a core control area, but machine identities require more continuous oversight than most human-centric programs provide. In practice, many security teams discover this only after a long-lived token, stale service account, or over-privileged integration has already been used to reach sensitive APIs.
How It Works in Practice
Effective governance starts by treating machine identities as first-class enterprise identities, not technical leftovers. That means inventorying every API consumer, service account, workload identity, certificate, and token issuer; assigning an owner; and mapping each identity to a business purpose. Without that baseline, least privilege cannot be enforced and review cycles become ceremonial.
From there, security teams should separate authentication from authorisation. A machine identity may prove who or what it is, but that does not justify broad standing access. Instead, access should be constrained by context: what workload is calling, from where, for which service, and for how long. This is where policy-driven controls and lifecycle discipline matter. The Top 10 NHI Issues highlights the recurring failure modes: stale credentials, excess privilege, weak monitoring, and poor visibility across environments.
- Use short-lived credentials where possible, and prefer automatic rotation over manual refresh.
- Bind each identity to a named owner, a defined workload, and a documented expiry or review interval.
- Enforce secrets storage in approved vaults, not code, config files, or build tooling.
- Log token issuance, API calls, privilege changes, and revocation events with alerting on drift.
- Reconcile cloud, SaaS, and internal API inventories so orphaned identities can be removed.
NIST SP 800-53 Rev. 5 is useful here because it translates governance into operational controls such as access enforcement, auditability, and configuration management. These controls tend to break down when identities are embedded in legacy integrations and shared service accounts because ownership, rotation, and revocation become too entangled to execute cleanly.
Common Variations and Edge Cases
Tighter machine identity control often increases operational overhead, requiring organisations to balance stronger governance against deployment speed and integration complexity. That tradeoff is real, especially in microservices, DevOps pipelines, and partner ecosystems where tokens are created and consumed at high velocity.
One common edge case is third-party OAuth access. A vendor may receive broad, persistent API access through an application grant rather than a conventional account, which means visibility and offboarding depend on both sides of the relationship. NHIMG’s State of Non-Human Identity Security reports that 85% of organisations lack full visibility into third-party vendors connected via OAuth apps, which is why these grants often survive longer than their intended use.
Another edge case is ephemeral cloud-native workloads. Best practice is evolving, but current guidance suggests using workload identity and automated issuance instead of embedding static credentials into images or pipelines. This is especially important when APIs are called by agents, batch jobs, or autoscaled services that do not follow human schedules. The control model must match the identity lifecycle, not the release calendar. In practice, governance becomes fragile when machine identities are created faster than review, because stale trust accumulates silently across environments and is usually found only during incident response.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Non-Human Identity Top 10 and CSA MAESTRO address the attack and risk surface, while NIST AI RMF, NIST CSF 2.0 and NIST Zero Trust (SP 800-207) set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP Non-Human Identity Top 10 | NHI-01 | Covers inventory and visibility gaps that make machine identity sprawl hard to govern. |
| CSA MAESTRO | ID-1 | Addresses identity lifecycle and governance for autonomous workloads and service identities. |
| NIST AI RMF | Supports governance of dynamic, AI-driven behaviour that can alter API usage patterns. | |
| NIST CSF 2.0 | PR.AA | Identity management and access control are central to governing API access by machines. |
| NIST Zero Trust (SP 800-207) | SA | Zero Trust is relevant because API trust should be evaluated continuously, not assumed. |
Use AI RMF governance to define accountability, monitoring, and escalation paths for machine-driven access.
